Neural modeling and simulation are foundational tools in computational neuroscience, enabling researchers to explore how neural systems process information, generate behavior, and adapt over time. These approaches range from detailed biophysical models of single neurons to large-scale simulations of brain networks, offering critical insights into both healthy and disordered brain function. As the field advances, there is a growing need to consolidate knowledge, compare methodologies, and reflect on emerging trends. This Research Topic provides a platform for experts to evaluate the current state of the field, highlight methodological challenges, and propose future directions. By gathering authoritative contributions across modeling scales and approaches, this Topic will support ongoing efforts to refine neural simulations and expand their role in understanding the brain.
Neural modeling and simulation are vital for understanding brain function, yet the field faces key challenges. Diverse modeling approaches ranging from detailed biophysical models to large-scale network simulations, can be difficult to compare, validate, or apply consistently. As models grow more complex, issues of scalability, transparency, and reproducibility also arise. Recent advances in computing, open-source tools, and data availability have improved model development and collaboration. However, there is a clear need for critical reflection on current methods, shared best practices, and future directions.
We welcome contributions that assess modeling approaches, highlight challenges, or propose forward-looking insights. The goal is to provide a curated, impactful resource that supports the ongoing development and refinement of neural modeling and simulation.
The collection invites articles focused on neural modeling and simulation across all scales - from single-neuron dynamics to large-scale brain networks. We welcome contributions that assess the state-of-the-art in biophysical modeling, spiking neural networks, functional connectivity, and brain simulations. Key themes include model validation, reproducibility, integration of experimental data, and the use of open-source simulation tools. We also encourage discussions on methodological advances, scalability, interpretability, and the role of neural modeling in understanding cognition and neurological disorders. Authors may also address challenges in bridging modeling scales, highlight promising trends, or propose future research directions. Interdisciplinary perspectives combining neuroscience, computer science, and applied mathematics are particularly welcome.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Conceptual Analysis
Data Report
Editorial
FAIR² Data
General Commentary
Hypothesis and Theory
Methods
Mini Review
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
